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All Journal Syntax Literate: Jurnal Ilmiah Indonesia KACANEGARA Jurnal Pengabdian pada Masyarakat Asean Journal of Sport for Development and Peace
Hapsari Peni
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Humanities Education Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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PUSH UP MONITORING SYSTEM USING ESP32 FOR REAL-TIME PERFORMANCE ANALYSIS Rusdiawan, Afif; Alamsyah, Sayyidul Aulia; Peni, Hapsari; Supriyanto, Catur
ASEAN Journal of Sport for Development and Peace Vol 4, No 1 (2024): Sport for Sustainable Development (January) 2024
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ajsdp.v4i1.67924

Abstract

Health and physical fitness are great concern to society today. One way to maintain health and physical fitness is by exercising. Recently, people seem very enthusiastic about exercising. We can see this from the frequent appearance of videos and photos of people’s sports activities on social media. One of the sports that many people do is push-ups. Many people are familiar with the push-up and often do it to train their arm muscles, or compete in endurance competitions between individuals. Even though they are often done, until now push-ups do not have an integrated monitoring tool so that they can become a credible medium for showing them off on social media. This research aims to create a push-up monitoring tool that can display data in real-time. The push-up monitoring tool is made using an ESP32 microcontroller which is equipped with a VL53L0X distance sensor. By using ESPNOW communication, the special communication between ESP microcontrollers, data can be sent from the push-up monitoring device to a receiver connected to a PC where the monitoring application is displayed. On the PC side, the application is designed to display graphs of distance chest to the ground, average height when the arms are straight, and average height when the arms are bent in real-time. These three aspects are important aspects for observing the validity of a push-up. The results of this research underscore the feasibility of the monitoring system in collecting push-up data. In addition, this research serves as a foundation for future research aimed at simplifying the push up monitoring systems.
Peningkatan Soft Skill berbasis kecerdasan tiruan untuk optimalisasi pemanfaatan energi renewable Three Kartini, Unit; Peni, Hapsari; Suprianto, Bambang; Buditjahjanto, I Gusti Putu Asto; Firmansyah, Rifqi; Anifah, Lilik; Nurhayati, Nurhayati
KACANEGARA Jurnal Pengabdian pada Masyarakat Vol 8, No 4 (2025): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/kacanegara.v8i4.2829

Abstract

berdasarkan kecerdasan buatan (Artificial Intelligence). Pelaksanaan pengabdian kepada masyarakat ini, dengan mengeksplorasi dari beberapa mahasiswa atau pelajar yang menggunakan AI dalam mengoptimalisasi pemanfaatan energi renewable. Ditemukan bahwa pelaksanaan pelatihan dari pelajar atau mahasiswa dengan menggunakan AI untuk tujuan umum dan akademis sehingga dapat lebih menguasai dan dapat mengaplikasikan AI dalam meningkatkan kehidupan sehari-hari. Dari perspektif umum, para peserta menggunakan AI untuk diaplikasikan dalam optimalisasi pemanfaatan energi renewable. Program ini dilaksanakan dengan tujuan untuk dapat meningkatkan serta dapat mengembangkan keterampilan dan kreatifitas pelajar dan mahasiswa terutama soft skill yang berbasis kecerdasan tiruan (AI) dalam mengoptimalisasi pemanfaatan energi terbarukan (renewable).  Sasaran utama dari pelaksanaan pengabdian kepada masyarakat ini adalah pelajar atau mahasiswa. Sosialisasi, workshop dan pelatihan yang telah diterapkan guna membantu peserta dalam memahami dan mengaplikasikan kecerdasan buatan (AI) untuk optimalisasi pemanfaatan energi renewable. Pengukuran tingkat keterpahaman peserta dengan menggunakan pre-test dan post test yang dievaluasi hasilnya. Dimana hasil evaluasi keterpahaman peserta dlam memahami materi dan aplikasi AI meningkat kurang lebih sebesar 35% dibandingkan dengan hasil pre test. Dan keseluruhan dari peserta sangat tertarik dengan optimalisasi pemanfaatan energi renewable berbasis kecerdasan tiruan (AI).
Hybrid KNN-LSTM Modeling for Short-Term Feeder Peak Load Forecasting Muhammad, Yasyfin Nur; Kartini, Unit Three; Peni, Hapsari
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v10i4.58191

Abstract

Load forecasting is important in power system planning and management. Accurate forecasting is key in maintaining the balance of energy supply and demand. This research develops a hybrid KNN-LSTM method for load forecasting using historical load and voltage data. KNN is used in finding local patterns and LSTM is used in capturing long-term patterns. The result is that the KNN-LSTM method provides MSE 30289.4952, RSME 174.0387, and MAE 98.9081. These results are better than the KNN and LSTM methods alone. In addition, by adding the voltage feature, the prediction result increases by 50.5%. Keywords: Load forecasting, KNN, LSTM, KNN-LSTM
Co-Authors Alamsyah, Sayyidul Aulia Catur Supriyanto I Gusti Putu Asto Buditjahjanto Lilik Anifah Muhammad, Yasyfin Nur Nurhayati Nurhayati Rifqi Firmansyah, Rifqi Rusdiawan, Afif Unit Three Kartini